There are approximately twenty million American children between the ages of seven and twelve in the United States, of which approximately ten percent (two million) are diagnosed with Attention deficit hyperactivity disorder (ADHD). Additionally, ten percent of children are diagnosed with specific learning disabilities (LD). Considering a twenty percent overlap in these two populations, there are approximately three and a half million children, ages seven to twelve, with ADHD, LD or both. Parents of ADHD and LD children encounter difficulty helping their children complete homework, keep their work organized, study for tests and practice reading. These children often refuse to perform other responsibilities, such as taking a shower, leading to arguments in the house.
Children with ADHD have difficulty sustaining attention unless the task at hand is compelling and entertaining. Likewise, children with LD are often frustrated with how difficult it is to learn, causing them to be disinterested and unfocused unless the learning is compelling and entertaining.
Since parents care so much about the education of their children, alternative teaching and mentoring experiences can fill an important role in facilitating a child's educational growth. For example, a robot can alleviate some of this burden and work with children in an engaging and fun way. The robot can teach reading, practice for tests (e.g. spelling and math), keep homework organized, encourage the completion of basic chores and play games with the children, all in a manner that capitalizes on the relationship the child develops with the robot. Since the robot can interpret a child's comment and respond with a psychologically sound comment, the child can develop a personal connection to the robot. As the robot fosters this connection, the robot can motivate a child to maintain positive feelings and behaviors while improving upon negative feelings and behaviors.
The need for robot-assisted education for children with learning disabilities is self-evident. There is thus a need in the field of data processing for improved methods, circuits, devices and systems for personality interpretation and expression.